DocumentCode
2221905
Title
Markov chain with fuzzy states: Application to queuing decision models
Author
de la Fuente, D. ; Pardo, M.J.
Author_Institution
Dept. of Accounting & Bus. Adm., Oviedo Univ., Gijon, Spain
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
173
Lastpage
177
Abstract
In this paper, we design a queuing system by calculating the best policy to be implemented regarding publicity decisions by using Markov chains with fuzzy states. To this end, first we calculate the steady-state probabilities when the states of the Markov Chain become fuzzy, and next we illustrate by an example the theoretical results previously obtained. In the example, we apply the linear programming solution to the Markovian decision process.
Keywords
Markov processes; decision making; decision theory; fuzzy set theory; probability; queueing theory; Markov chain; fuzzy state; queuing decision model; steady-state probability; Computational complexity; Costs; Dynamic programming; Fuzzy sets; Fuzzy systems; Joining processes; Linear programming; Probability; Queueing analysis; Steady-state; Fuzzy sets; Markov chain; queuing theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-2629-4
Electronic_ISBN
978-1-4244-2630-0
Type
conf
DOI
10.1109/IEEM.2008.4737854
Filename
4737854
Link To Document